BIOMETRIC CRYPTOGRAPHIC AUTHENTICATION IN …International Journal of Computational Science,...

International Journal of Computational Science, Information Technology and Control Engineering (IJCSITCE) Vol.3, No.1/2, April 2016

DOI : 10.5121/ijcsitce.2016.3204 35

BIOMETRIC CRYPTOGRAPHIC AUTHENTICATION IN

PERVASIVE ENVIRONMENT

Rachappa1, DivyaJyothi M G

2 and Dr. D H Rao

3

1Research Scholar, Department of Computer Science, Jain University, Bangalore

2Research Scholar, Department of Computer Science, Jain University, Bangalore

3Professor and Dean, S.G. Balekundri Institute of Technology, Belgaum

ABSTRACT

Day by day technology is moving towards advancements and pervasive computing environment is leading

where the users can get services everywhere. The ubiquity of the smart spaces brings new security

challenges, in which the user and the service provider have to be authenticated with the strong

authentication technique. In this proposal, a very flexible common authentication scheme based on

biometric encryption to protect communications between a user and a service provider is proposed. In this

proposal, user’s hidden authentication is achieved.

KEYWORDS

Privacy, Security, Biometric encryption, Pervasive Computing, RSA, RSA cryptography, Biometry and

Cryptography

1. INTRODUCTION

Computer technology increasingly advances and it come into everyone’s lives more and more as

they perform better and we can do several tasks faster with them. Day by day as a result of

computing devices becomes increasingly smaller, tiny and powerful, the embedded technology

leads the role. The aim is to meet the claim of “anywhere, always, everywhere” for data

processing and communication through the ubiquity of information and communication

technologies.

Towards Mark Weiser’s vision[1][2][7][8][22], pervasive computing is the next generation of

computing environments with information and communication technology anywhere, anytime for

all. Pervasive computing proposes the assurance of simplifying daily life by incorporating mobile

devices and digital infrastructures into our real world. With the help of several sensors and

embedded devices, active spaces can automatically be combined to users’ preferences and can

capture and utilize context information. Sometimes, this feature could threaten the privacy of

users rigorously and raise the issues of information misuse. For example, this feature can be

misused by intruders, hackers, malicious users of insiders, sometimes system administrators to

thread users. Undoubtedly, for preserving users’ privacy is much more difficult task in pervasive

environment.

Pervasive computing technology will surround users with a contented and convenient information

environment that combines physical and computing devices into an integrated environment. This

feature will upsurge the productivity and interaction. Context awareness will allow this


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environment to take on the responsibility of serving users, with combined activities according to

the nature of the physical space. The stated setting is called as “active space”, [7][8][11] in

which, users can relate with number of applications which may follow the user orders, and

control the numerous flexible applications that may obey the user, define and control the active

space.

A pervasive computing environment unexceptionally and transparently supports the human

beings with its uninterrupted computation and communication [7]. This computation power

guarantees transparent interaction of the devices with the users [8][2]. In pervasive computing

environment, control over collection and dissemination of information is perceived through

privilege of users, which is in turn called as privacy in PCE and these users can be categorized as

individuals, groups, or organizations.

Normally, the basic security mechanism involves static network or closed system with the central

control, whereas the Pervasive computing environments mutual communications are unexpected

and are dynamically active. The communication channel will be established between a user and a

service provider. Subsequently, before to the access of services, a mutual agreement between

users and service providers should be established.

Increase in location based applications guarding personal location information has become a

foremost challenge. In order to resolve this matter, a set of procedures and guidelines are required

which should allow users to control their location information predictably. With the major

concern about privacy and security in pervasive computing environments, ample research has

been conducted concentrating on various aspects [3].

2. PRIVACY IN PERVASIVE COMPUTING ENVIRONMENTS Privacy in Pervasive Computing is a major issue. Numerous models have been proposed and

come up with several solutions to address privacy challenges. The successful project proposal

needs the desires and consciousness of the users’ requirements. The tedious and complicated

proposals of pervasive environments are embedded or they are invisible.

In pervasive computing environments, the ‘invisible’ computing devices are increasingly

gathering personal data and deriving user context, the user will be concerned with their privacy

and security. Devices may reveal and exchange personal and sensitive information (such as

identity, role, preferences, credentials, etc) with the smart objects in pervasive systems. Privacy

in pervasive environment will be a major issue, when the devices cannot belong to a one trusted

domain. It is a critical situation to develop and create privacy sensitive services in pervasive

computing systems to increase the real benefit of these technologies and decrease possible and

actual risks. Since these systems gather a large amount of personal sensitive information (such as

e-mail id, shopping history, location, etc.) and showing people’s negligible interest in

participating pervasive environments.

Henceforth, in order to maintain privacy at all times, it has become mandatory to design proper

procedures and guidelines.

Privacy can be well-defined, according to Steffen et al. [4], as “An entity’s ability to control the

availability and exposure of information about itself”. In [5], the authors identify five important


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key features which make these systems very different from the current data collection systems

[3]. They are:

1. Innovative and State-of-the-art computing technologies and objects will be presented in

active space.

2. Data collection will be invisible and unnoticeable;

3. The gathered data will be more friendly than ever before;

4. The underlying motivation behind the data collection;

5. The necessary interconnectivity for smart devices to cooperate for providing service

to users;

2.1 Anonymity

The actual identity of the user should never be disclosed from the communications exchanged

between the user and a server unless it is deliberately revealed by the user.

In order to analyze the secrecy mechanisms with regard to device flexibility, the author,

Zugenmaier et al. [6] proposed a new attacker model, “Freiburg Privacy Diamond Model (FPD)”.

Figure1. Sample Privacy Model [9]

The sample privacy model will perform four types of entities to distinguish information about

secrecy, that are - the performed action ‘a’, the device ‘d’ used for performing the action, the user

‘u’ that performs the action and the location ‘l’ of the device, as depicted in Figure 1. The authors

are clearly described the relationship of each entities, and the attacker familiarization with the

existing relationship to break the secrecy/anonymity.

2.2 Confidentiality and Integrity Confidentiality refers to the need of keeping information secure and confidential. Integrity refers

to the concept of protecting information from being inappropriately modified by unauthorized

users.

2.3 Unobtrusive

The main aim of pervasive computing is to be anonymous and unobtrusive. The computing

technology is embedded into everyday smart objects that communicate information. This concept


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of embedding reduces the visibility of the pervasive computing environment and makes the

technology more friendly and adequate to the user.

Consequently, the same characteristic will invade the privacy of the user without the user

realizing it.

2.4 Location Dependency The Pervasive computing technologies make use of location information such as traffic reports,

navigation maps, news, locating nearest restaurants, nearest clinics, etc. [12]. The users have to

provide these information to the service provider.

2.5 Context Dependency

The Pervasive computing tools are dependent on context information, such as the type of wireless

device used, user profiles, user preferences, current time, GPS coordinates etc. [13] [23].

Protecting context information is a tedious task, as they deal with different sets of information

with context aware systems.

2.6 Data Collection

A pervasive computing application relies on an large amount, quality, and accuracy of data

generated and collected. Also most of the pervasive computing technologies include wireless

devices and these devices are limited to processing power, throughput, bandwidth, memory etc

[14].

2.7 The Service Provider

Maintaining the privacy of data is very crucial for service provider. Chances and vulnerabilities

for misuse of data is more. In reality, its difficult to ensure that all the service providers follow

the rules.

The author, Langheinrich [15] measured, designing a perfect mechanism for protecting privacy

would be hard to achieve. Subsequently, the author proposed a system, for alerting users about

their privacy. The proposed system depends on social and legal principles of real life, rather than

designing a system to ask and respect the users’ privacy. The publisher named the system as, the

privacy awareness system (pawS), which allows data collectors to process personal data, sensitive

data and organization policies, and data manipulation tools such as adding, deleting and

modifying information

The developed pawS architecture consists of two main parts: privacy proxies and a privacy aware

database.

Privacy proxy:

This proxy is developed to allow the automatic interchange and auto update of privacy policies

and client information. This is proxy is developed and implemented to run on a web server using

group of services called Simple Object Access Protocol (SOAP) protocol. In this protocol all the

user’s requests are responded by the service proxies.


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Privacy aware database:

This is known as pawDB. This protocol combines the users’ privacy policies and their collected

data elements into a sole component of storage space which then handles the data according to the

usage policy.

3. ASSOCIATED WORK Many authors have proposed numerous proposals and models to address the concerns of privacy

protection in pervasive computing environment. In this paper, we propose a unique scheme for

privacy preserving authentication in pervasive computing environments.

4. SYSTEM ARCHITECTURE Biometric cryptographic authentication with RSA algorithm is used to authenticate in our

scheme. This approach is different from the existing conventional approaches. In this approach

we integrate the techniques of cryptography and biometrics effectively for maintaining privacy

and secrecy of the data.

4.1. Biometry and Cryptography Many researchers have studied and proposed the interface between two corresponding

technologies, biometrics and cryptography. Biometrics is about determining unique personal

features, such as a face recognition, voice recognition, fingerprint, signature, hand geometry, or

iris.

The general Biometric system [16][21] is described in Figure 2. As illustrated in the picture, its

authentication has to be transparent and trusted. The major advantages of biometrics are

uniqueness, and need not to remember passwords. Biometrics is what you have, and it cannot be

stolen or forgotten.

The Biometric technique is shown in Figure 3.


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Figure 2: General Biometric System

Figure 3: Biometric Hashing

In the recent days, rapid growth has been observed in mobile computing with miniature devices.

[17]. The following Figure 4 depicts the pollution monitoring application using Cell Phone based

Sensor Network (CPSN) developed in [18] uses short-range communication outlets such as Wi-Fi

or Bluetooth


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Figure 4: Cell phone based sensor network.

On the other hand, Cryptography is where security engineering meets mathematics.

Cryptography provides numerous methods, algorithms and protocols to maintain authenticity.

Possibly, it uses key enabling technology for protecting distributed systems. It mainly concerns

itself with the projection of trust: with moving the trusted data from where it exists to where it is

needed.

A strong combination of biometrics and cryptography in pervasive environment would have

strong authentication scheme. It will be a tedious task to break the security and authenticity using

stolen token.

5. THE PROPOSED SYSTEM

We proposed system which aims to provide mutual authentication between user and Pervasive

computation devices. The scheme integrates Biometric Encryption and RSA key exchange

algorithm for authentication and key generation. The scheme holds most of the security

properties, such as anonymity, confidentiality, etc. system uses the RSA algorithm for key

generation. The solution implants biometric information on the private/public keys generation

process. Also the corresponding private key depends on biometric features and it can be

generated when it is needed. Starting from the fingerprint acquisition, and all the behavioural

biometric features, the biometric identifier is extracted, cyphered.

5.1 RSA Algorithm

The cryptographic algorithm was introduced by (RSA) Ron Rivest, Adi Shamir, and Leonard

Adleman, in 1978. RSA algorithm implements on a public key cryptosystem, and digital

signatures. Basically, RSA is inspired by the published work of “Whitfield Diffie” and “Martin

Hellman” for quite a long ago, they introduced new method of distributing cryptographic keys,

and it was known as Diffie–Hellman key exchange.


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RSA algorithm implemented two key concepts:

5.1.1. Public key encryption. This encryption mechanism introduces the concept of involving two keys - one for encrypting,

and the other for decrypting; only the user with proper decryption key can decrypt and encrypt the

message, since in RSA encryption keys are public, and decryption keys are private. The generated

keys must have a property of non-repudiation and cannot be easily assumed from the public

encryption key. The keys are to be transmitted to recipients over a secure channel.

5.1.2. Digital signatures. It is a mathematical scheme for authenticating a message or documents. The received message to

be verified by the user, whether the transmitted message is generated by the sender. A valid

digital signature provided the originality of the message transmitted by sender and provided

authenticity that the message was not modified during the transmission. Normally this technique

is used to implement electronic signatures.

The security of the RSA algorithm is validated, and mostly no attempts were able to break it,

since it is difficult to find out the two large primes p and q, from the number n=pq.

5.1.3 Public-key cryptosystems

Let us assume that, each user has their own encryption and decryption procedures, En (public

key) and Dn (Secret key). In RSA algorithm, these two procedures are denoted as two numbers.

Let us assume that Msg is a message to be encrypted. We follow four statements which are

essential to a public-key cryptosystem

a) Deciphering an enciphered message gives you the original message, symbolically

Dn(En(Msg)) = Msg

b) Reversing the procedures still returns M

En(Dn(Msg)) = Msg ….. (2)

c) En and Dn are easy to compute.

d) The publicity of En does not compromise the secrecy of Dn, meaning you cannot

easily figure out Dn from En.

With a given En, we are still not given an efficient way of computing Dn.

We know that, if Ct = En(Msg) is the cipher text, then computing Dn and to satisfy the Msg in

En(Msg) = Ct is arbitrarily difficult.

The above properties prove that, it is trap door one way permutation, For example, the users ALC

and BOB (Alice and Bob) on a two user public key cryptosystem, with their keys: EALC, EBOB,

DALC, DBOB.

5.2 RSA Cryptography: Key Generation in Pervasive environment

The following steps to be followed for RSA key generation


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1. Produce two prime numbers p and q

2. Find n = p × q

3. Find Φ(n) = (p − 1) × (q − 1)

4. Select e, such that 1 < e < Φ (n) and gcd(Φ (n), e) = 1, where e is an exponent

5. Calculate d such that d = e−1 mod Φ (n), where d is a private exponent

6. Public Key = [e, n]

7. Private Key = [d, n]

5.3 RSA Cryptography: Selecting the Primes p and q

Firstly we need to decide the size of the modulus integer n. Let us assume that our

implementation of RSA needs modulus of size B bits.

In order to generate the prime integer p;

– Generate a random number of size B/2 bits.

– Set the lowest bit of the integer generated by the above step, random number

generator; this ensures that the number will be odd.

– Set the two highest bits of the integer; and ensure that the highest bits of n will be set.

–Check the resulting integer is prime or not. If the resultant integer is not a prime, then

increment it by 2 and check again.

This becomes the value of p.

Follow the above steps for selecting q.

• If we get p = q, omit the generated random number, and find the new one.

• If the resulting integer is not a prime, then re generate the new random number, rather than

increment by 2

5.4 Efficient encryption and decryption operations.

The RSA algorithm states that “Computing Me(mod n) requires at the most 2·log2(e)

multiplications and 2·log2(e) divisions”. It is important to find the amount of steps it would take a

computer to encrypt the message so, it can be evaluated the performance of the algorithm. The

method follows:

Step 1. Let ek ek−1....e1e0 be the binary representation of e.

Step 2. Set the variable C to 1.

Step 3. Repeat steps 3(i) and 3(ii) for i = k, k − 1, ..., 0:

Step 3(i). Assign C = C2 mod n

Step 3(ii). If ei = 1 then, assign C to the remainder of C·M when divided by n.

Step 4. Halt. Hence C is the ciphertext of M

There are many proposed procedures exists, but we found this is the better algorithm. More

importantly, the decryption technique follows the similar unique procedure as encryption, and

can be implemented the whole process on a few integrated chips.

As per the RSA, it claims that “the amount of encryption time per block rises no faster than the

cube of the number of digits in n.


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6. BIOMETRIC RSA SYSTEM: EXAMPLE SCENARIO IN PERVASIVE

ENVIRONMENT The proposed system is used to generate key. In this proposal, we combine the features of

biometrics based on RSA algorithm. Basically it is composed of fingerprint authentication

module, asymmetric cryptography module.

It is depicted in the following Figure.

Figure: Biometric RSA System

6.1 RSA Biometric: The method includes the following features;

i) The biometric private key is randomly generated and not stored in any device, and using the

fingerprint characters stored in user smartcard during the enrolment phase.

ii) Damage proof smartcards and Cryptography provide a secure environment and protect from

unauthorized access to smartcard devices,

iii) It also protects the confidentiality of the biometric information. So, the private key cannot be

misplaced and stolen.

iv) Fingerprint image quality, affecting systems performance, can be checked during the

enrolment phase.

In the enrolment phase, the biometric trait is acquired and processed to extract its own distinctive

features.

i) Biometric trait representation is encrypted and stored in tamper-resistant device,such as,

smartcard.

ii) During the authentication phase, the enrolled biometric identifier is used together with the

query biometric identifier for user authentication and public/private key pair generation.

iii) The link between biometric traits and the cipher algorithm is a pair of prime number.

6.2 Signatures with RSA:

Say Bob (=B) and Dave =(D) are using RSA. In a public key cryptosystem, there is no shared key

that only Obama and Cameron have. So Verda (=V) could email Bob an AES key, encrypted with

Bob’s public RSA key and then send Bob the message “Hello Verda, sincerely, Dave” encrypted

with AES. How would Bob know whom it’s from, he must demand a signature. [20]


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Case 1, D sends PT msg M to B, no need to encrypt. At end signs M2 =‘Dave’. Wants to make

sure B knows it is from him. C then computes M2dC mod nC = S. Could add to end of msg. Only C

can do that. The message can be verified by B, just by finding SeCmod nC in order to get M2. Eve

can read signature too. Also L can cut and paste signature to end of his own message.

Case 2. C creates an AES key and sends (keyAES)eB

mod nB to B. C encrypts message M for B

using AES and sends CT to B. C hashes M to get H=hash(M). C computes HdC

mod nC = S and

sends to B. B decrypts using RSA to get keyAES. B decrypts CT with AES to get M. B hashes

(decrypted) M to get H. B compute SeC

(mod nC) and confirms it equals H he earlier computed.

Only C could have created an S so that SeC

= H. If it does, then B knows 1) the message was sent

by whoever owns the keys eC and nC (authentication) and that it was not tampered with by anyone

else (integrity). Note that V has access to H. B and C may not want that. So C may encrypt S with

RSA or AES.

Case 3. Same as case 2, but B and C do not want V to have access to hash(M) (for whatever

reason - maybe C will resend M to someone else). So C encrypts S using AES.

7. RSA - THE SECURITY SYSTEM

Pervasive security environments demands high degrees of security for its deployment and RSA

based hardware and software products can be very much used for the secure communication and

authentication. Already RSA based security employee tokens are widely in use in various

companies. The uniqueness of this token lies in the fact that the public key generated by these

tokens vary every time one runs it. This along with any other biometric trait can make a strong

authentication identifier.

8. CONCLUSION

In this paper, we propose a biometric authentication using RSA cryptographic algorithm. We

discussed the key establishment scheme using biometrics for Pervasive computing environments.

The proposed authentication mechanism is efficient in solving the conflict between privacy

protection and authentication, which usually needs the users’ sensitive information. Explicit

mutual authentication is achieved among the service providers and users by following this

approach. This scheme is effective in maintaining the anonymity and confidentiality of the user.

As a result, the approach proposed can serve very well in pervasive computing environments.

9. ACKNOWLEDGMENTS

We would like to thank our Professor Dr. D. H. Rao for the patient guidance, encouragement,

and time given during the course of our work.

10. REFERENCES

[1] M. Weiser. The computer for the twenty-first century. Scientific American, 265(3): 94-104, 1991.

[2] Juan Ye and Simon Dobson. “Pervasive Computing needs better situation –awareness” ,

doi:10.2417/3201201.003943


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[3] Ameera Al-Karkhi1, Adil Al-Yasiri2 and Nigel Linge, “Privacy, Trust and Identity in Pervasive

Computing: A Review of Technical Challengesand Future Research Directions” Department of

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[4] Steffen, S., Bharat, B., Leszek, L., Arnon, R., Marianne, W., Morris, S., et al., (2004) “The pudding of

trust”. IEEE Intelligent Systems, 19(5), 74-88.

[5] Saadi, L., Marc, L., & Carsten, R., (2005) “Privacy and trust issues with invisible computers”.

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[6] Zugenmaier, A., Kreutzer, M., & Muller, G., (2003) “The Freiburg privacy diamond: An attacker

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[16] Khusvinder Gill, Shuang-Hua Yang, Fang Yao, and Xin Lu,”A ZigBee Based Home Automation

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[17] T. Abdelzaher, Y. Anokwa, P. Boda et al., “Mobiscopes for human spaces,” IEEE Pervasive

Computing, vol. 6, no. 2, pp. 20–29, 2007.

[18] D. Chander, B. Jagyasi, U. B. Desai, and S. N. Merchant, “Spatio-temporally adaptive waiting time

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Article ID 962476, 21 pages, 2011.

[19] Evgeny Milanov, The RSA Algorithm, 3 June 2009

[20] Edward Schaefer, “ An introduction to cryptography and cryptanalysis”, Santa Clara University

[21] M Varaprasad Rao1 and Prof N Ch Bharta Chryulu2, “ SECURED SMART SYSTEM DESING IN

PERVASIVE COMPUTING ENVIRONMENT USING VCS International Journal of UbiComp

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AUTHORS

Mr. Rachappa is currently working as Lecturer at the Department of Information

Technology, Al Musanna College of Technology, Sultanate of Oman. His teaching

interests include Computer Security, Pervasive Computing, E-Commerce, Computer

Networks, Intrusion detection System, Network Security and Cryptography, Internet

Protocols, Client Server Computing, Unix internals, Linux internal, Kernel

Programming, Object Oriented Analysis and Design, Programming Languages,

Operating Systems, Web Design and Development, etc. His most recent research focus

is in the area of Security Challenges in Pervasive Computing. He received his Bachelor

Degree in Computer Science from Gulbarga University, Master of Science Degree

from Marathwada University and Master of Technology in Information Technology Degree from Punjabi

University (GGSIIT). He has been associated as a Lecturer of the Department of Information Technology

since 2006. He has worked as Lecturer at R.V. College of Engineering, Bangalore. He has guided many

project thesis for UG/PG level. He is a Life member of CSI, ISTE.

Mrs DivyaJyothi M.G. is currently working as Lecturer at the Department of

Information Technology, Al Musanna College of Technology, and Sultanate of Oman.

Her teaching interests include Pervasive Computing, Firewalls and Internet Security

Risks, E-Commerce, Computer Networks, Intrusion detection System, Network

Security and Cryptography, Internet Protocols, Client Server Computing, Unix

internals, Linux internal, Kernel Programming, Object Oriented Analysis and Design,

Programming Languages, Operating Systems, Image Processing, Web Design and

Development, etc. Her most recent research focus is in the area of Pervasive

Computing. She received her Bachelor and Master Degree in Computer Science from Mangalore

University, She bagged First Rank in Master’s Degree at Mangalore University. She has been associated as

a Lecturer of the Department of Information Technology since 2007. She has worked as Lecturer at ICFAI

Tech., Bangalore, T John College for MCA, Bangalore, Alva’s Education Foundation Mangalore. She has

guided many project thesis for UG/PG level.

Dr. D H Rao is Currently working as Professor and Dean, S.G. Balekundri Institute of

Technology, Belgaum. He has worked as a Dean, Faculty of Engineering, VTU,

Belgaum. He was Principal at KLS Gogte Institute of Technology, Belgaum and Jain

College of Engineering, Belgaum. He is the Chairman, Board of Studies in E & C

Engineering, VTU, Belgaum. He is a Member, Academic Senate, VTU Belgaum. He

has over 100+ publications in reputed Journals and conferences. He obt ained B.E. (in

Electronics from B.M.S. College of Engineering), M.E. (from Madras University),

M.S. (University of Saskatchewan, Canada) Ph.D. (Univ. of Saskatchewan, Canada).

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